Epic: Library-wide feature tiers and production-readiness contract

Start by reviewing the README feature catalog and the existing xrspatial.geotiff.SUPPORTED_FEATURES runtime mapping. Map the public callables, documented accessors, backend or algorithm variants, and available evidence before proposing the library-level registry. Done means the tier vocabulary, registry schema, documentation checks, tests, and GeoTIFF compatibility path are defined across the stated scope.

Goal

Adopt the GeoTIFF feature-tier strategy across the full xarray-spatial
library so users can distinguish what is production-ready from what is useful
but still maturing.

The library now advertises 150+ functions across raster I/O, reprojection,
surface analysis, hydrology, flood, fire, interpolation, raster/vector
conversion, classification, focal operations, proximity, MCDA, and utility
layers. The README already documents backend availability (NumPy, Dask,
CuPy, and Dask+CuPy) and sometimes signals individual experimental tools.
It does not yet communicate one consistent answer to the more important
question: what behavior can a production user rely on?

GeoTIFF provides a working precedent:

• tier strings with clear meanings;
• a runtime source of truth (xrspatial.geotiff.SUPPORTED_FEATURES);
• documentation that mirrors the runtime mapping;
• narrow stable contracts backed by regression/release-gate tests;
• explicit opt-in for particularly risky experimental or internal paths;
• explicit unsupported combinations rather than overclaiming.

This epic generalizes that approach for every public tool and meaningful
subfeature without claiming that all existing functions or all their backends
are stable on day one.

Product Outcome

After this work, a user evaluating a workflow such as Dask hydrology, GPU
terrain generation, rasterization, kriging, or MCDA should be able to answer:

• Is the tool stable, advanced, experimental, internal, or
  unsupported?
• Does that tier apply to the core NumPy behavior only, or also to Dask/GPU
  implementations?
• Are important modes, algorithms, options, data shapes, or integrations at a
  different tier from the tool's default path?
• What correctness, parity, scalability, and interoperability behavior has
  actually been tested?
• What must happen before an advanced or experimental path can be promoted?
• Will a breaking change be deprecated, release-noted, or allowed to change
  while the feature matures?

The result is a user-facing production-readiness contract, not a marketing
badge or a claim that experimental tools are low quality.

Scope

In scope

• Every public callable exported from xrspatial, public subpackages
  (hydro, mcda, interpolate, reproject, geotiff, and
  experimental), and documented .xrs accessor methods.
• Every user-visible tool in the README function catalog, including functions
  which are documented but are not currently top-level exports.
• Material subfeatures whose maturity can differ from their parent callable:
  algorithms/methods, input/output modes, distributed or GPU backends,
  remote/external integrations, metadata behavior, optional-dependency paths,
  and compatibility aliases/wrappers.
• Documentation, API representation, test evidence, promotion/demotion rules,
  release-process integration, and contribution policy.

Out of scope

• Rewriting implementations simply to make all tools stable.
• Treating backend availability as proof of production readiness.
• Tiering private helpers, internal kernels, or implementation-only utilities
  unless they define a public behavior contract.
• Guaranteeing numerical identity between fundamentally different algorithms;
  the contract must state the relevant tolerance/behavior instead.
• Replacing ordinary semantic-versioning and deprecation policy. Tiers make
  that policy legible; they do not remove it.

Tier Semantics

The library catalog should use five consistent status values:
stable, advanced, experimental, internal, and unsupported.
The first three describe adoptable public functionality at different levels
of maturity. internal and unsupported make boundaries visible so internal
implementation paths and deliberate non-features cannot be mistaken for
production promises.

stable

A supported production contract:

• public behavior, accepted input domain, output semantics, and documented
  metadata/coordinate behavior are defined;
• the promised backend(s) have focused regression tests in normal CI;
• distributed/GPU parity or stated numerical tolerance is tested when those
  backends are part of the stable contract;
• error behavior for unsafe or unsupported inputs is tested where material;
• breaking changes require deprecation/release-note handling under project
  policy;
• stable claims are checked during release readiness.

stable does not mean every optional mode or every backend of that callable
is stable. For example, tool.slope could be stable for CPU and Dask while
tool.slope.backend.cupy remains advanced until its parity evidence is
recorded.

advanced

A usable, documented feature for informed production adoption:

• implementation exists and has meaningful tests;
• supported input/mode limitations are documented;
• users may deploy it when they can validate results and follow migration
  notes;
• the surface, uncommon edge-case behavior, performance envelope, or
  cross-backend parity may not be fully pinned down;
• breaking refinements before a stable promotion must be called out in
  release notes, but do not necessarily require the full stable guarantee.

experimental

An evaluation-stage feature:

• it is visible so users can try it and provide feedback;
• it has at least smoke/validation coverage appropriate to its current risk;
• its behavior or API may change without a deprecation window;
• production reliance is not recommended;
• experimental status must be visible at the import/docs/README touchpoints,
  and an opt-in may be appropriate where accidental use creates a significant
  correctness, interoperability, cost, or safety risk.

internal

An internal path exists to support library implementation needs or one
deliberately narrow xrspatial use case, but is not an adoptable public
production contract:

• it may be documented where users can encounter it, so its boundary is clear;
• it must not be advertised as a normal public tool or as production-ready;
• if it is callable through a public entry point, accidental use should be
  blocked by an explicit opt-in or an equally strong guard when misuse is
  consequential;
• compatibility and external interoperability are not promised unless stated
  separately.

GeoTIFF JPEG-in-TIFF is the motivating existing example. At the library
policy level this should be called internal, not internal_only.

unsupported

An unsupported capability or combination is explicitly outside the
library's contract for the current release:

• it is recorded when users could reasonably otherwise assume support from a
  broader tool or backend claim;
• calling it should fail with an actionable error whenever returning a result
  would mislead users, lose information, or silently produce incorrect output;
• a documentation-only unsupported entry is acceptable where there is no
  executable path to guard;
• it cannot be presented as an adoptable tool until implemented, audited, and
  moved to an appropriate public tier.

Examples include meaningful method/backend combinations not implemented for a
tool, or GeoTIFF write combinations deliberately outside the current contract.

Classification Unit: Tool Plus Subfeatures

A single tier on a callable is insufficient when a function dispatches over
four backends or exposes algorithms with different confidence levels. Use a
two-level model:

1. Core tool tier: the documented default or narrowest recommended
   production path for the callable, with its backend/input scope stated.
2. Subfeature overrides: only for dimensions whose evidence or risks
   materially differ from that core contract.

Examples of subfeature dimensions to audit:

Dimension	Representative examples
Backend	numpy, dask, cupy, dask_cupy, CPU fallback behavior
Algorithm/method	D8/D-infinity/MFD; resampling modes; kriging variograms; MCDA combination methods; classification methods
Execution mode	lazy/chunked behavior, memory-bounded streaming, tiled processing, GPU strict/fallback mode
Input/output contract	nodata/NaN semantics, dtype behavior, coordinates/CRS, multi-band/multidimensional input, vector geometry validity
Integration	optional dependency, remote data/grid downloads, GeoTIFF/COG/VRT, DataArray/Dataset accessor surface
Risk-sensitive behavior	stochastic seeding, approximate computation, overflow/precision, security/resource caps, external interoperability

Do not explode the registry into a row for every parameter value. Create an
override only when it changes what a production user may safely conclude.

Proposed Source Of Truth

Introduce a library-level machine-readable registry, provisionally:

from xrspatial import FEATURE_SUPPORT

FEATURE_SUPPORT["surface.slope"]
FEATURE_SUPPORT["surface.slope.backend.dask"]
FEATURE_SUPPORT["hydrology.flow_direction.mfd"]
FEATURE_SUPPORT["raster_vector.rasterize.backend.cupy"]

The implementation PR should settle the precise name/module and schema. The
schema must support more than a bare tier string because the GeoTIFF model is
being expanded across heterogeneous tools. Minimum fields:

Field	Purpose
tier	stable, advanced, experimental, internal, or unsupported
public_api	Canonical import/callable or documented accessor path
category	README/reference-doc grouping
scope	Plain-language boundary of what the tier covers
subfeatures	Backend/method/mode overrides, if any
evidence	Test file(s), parity/golden-reference suite, benchmark/resource check, or tracked gap
limitations	Known boundaries and unsupported combinations
owner_issue	Audit/promotion/follow-up issue responsible for the classification

Requirements for the registry:

• one canonical key naming convention with aliases pointing at canonical
  entries rather than duplicating tier decisions;
• existing xrspatial.geotiff.SUPPORTED_FEATURES is either incorporated
  without breaking public consumers or bridged into the library registry;
• the library-level vocabulary uses internal; the implementation plan must
  decide how GeoTIFF's existing runtime internal_only value migrates or is
  compatibility-aliased without silently breaking callers;
• unsupported entries may describe deliberate combinations rather than
  callable implementations, but remain queryable/documentable through the
  same status model;
• import-time footprint remains small: the registry cannot import optional
  GPU/geospatial dependencies or trigger compute/network work;
• docs tables are rendered from or checked against this source of truth;
• missing public APIs and unrecognized tier strings fail CI;
• users can inspect status programmatically without parsing documentation.

Audit Rubric

Classification should be evidence-based and deliberately conservative. Every
tool audit records the following:

Area	Questions
Public/API surface	Is the documented import path intentional? Are aliases and unified wrappers clear? Is the signature/docstring coherent?
Correctness baseline	Is behavior compared to a published algorithm, trusted implementation, hand-computed fixtures, invariants, or golden outputs?
Input contract	Are dtype, NaN/nodata, coordinate/grid, dimensionality, invalid-input, and boundary behaviors specified and tested?
Backend contract	Which README-advertised backends are native, fallback, untested, approximately equivalent, or parity-tested?
Dask behavior	Is it actually lazy? Are chunk boundary results correct? Are graph/memory risks bounded for large rasters?
GPU behavior	Does it have device-available CI/smoke coverage and defined tolerance versus CPU? Is fallback visible rather than silently changing expectations?
Numerical/algorithm modes	Do mode-specific algorithms need separate tiers or tolerances?
Performance/resources	Can ordinary production-sized inputs unexpectedly allocate unbounded memory, trigger downloads, or scale unexpectedly?
Safety/interoperability	Are file/network/vector/metadata/optional-dependency interactions constrained and failure modes actionable?
Documentation	Are tier, scope, limitations, examples, and production guidance visible where users encounter the tool?

Initial classification rules:

• Do not infer stable from age, popularity, top-level export, or a green
  unit-test file.
• Default an unaudited public tool to experimental or unclassified
  during migration; do not silently label it stable.
• Mark a path internal only when it is intentionally not an adoptable
  public contract; mark a combination unsupported when users need an
  explicit negative answer rather than a maturity label.
• A tool may become stable for its narrow NumPy path before the remaining
  advertised backends are promoted.
• A CPU fallback on a GPU/Dask input is a documented execution mode, not
  native backend parity; classify it separately when it affects performance
  or scalability expectations.
• For wrappers (for example unified hydrology entry points), the wrapper
  cannot have a stronger broad claim than the algorithms/backends it selects;
  its stable scope can explicitly identify the stable choices.

Workstreams By Library Area

The audit should be divided into owned, reviewable batches based on the
current README/reference layout:

Workstream	Surfaces to classify
Existing precedent	GeoTIFF/COG/VRT mapping and compatibility with the new library registry
Georeferencing and grid transforms	Reproject, merge, resample; projection/datum/vertical-shift methods and backends
Terrain/surface/visibility	Aspect, slope, hillshade, terrain metrics, viewshed/visibility, synthetic terrain/noise/erosion/bump
Hydrology and flood	D8/D-infinity/MFD families, unified wrappers, HAND/TWI, flood and vegetation-driven flood tools
Raster/vector and spatial movement	Rasterize, polygonize, contours, polygon clip, proximity, surface distance, cost/corridor, pathfinding
Neighborhood/image analysis	Focal, bilateral, GLCM, edge detection, morphology, sieve, diffusion
Statistical/domain analytics	Classification, multispectral, fire, KDE, multivariate, dasymetric, interpolation, MCDA
Cross-cutting public surfaces	Utilities, accessors, diagnostics, dataset interactions, optional dependency and backend-fallback behavior

Each workstream should produce classification entries, supporting evidence
links, documented gaps, and focused follow-up issues for anything that needs
hardening before promotion.

Phased Implementation Plan

Phase 0: Establish policy and design the registry

Deliverables:

• Add a short library-level feature-support policy document defining all five
  statuses: stable, advanced, experimental, internal, and
  unsupported.
• Decide the registry location, schema, canonical key grammar, alias strategy,
  treatment of .xrs accessors, and whether an interim unclassified status
  is required during rollout.
• Define what stable means for API changes, numerical tolerances, lazy
  behavior, fallback behavior, optional dependencies, and release blocking.
• Decide how generated docs/reference tables consume or validate the
  registry.
• Decide which risky experimental paths require explicit runtime opt-in
  versus conspicuous documentation only, and apply the same decision to
  publicly reachable internal paths.
• Decide the compatibility migration from GeoTIFF's current
  internal_only runtime spelling to the library-wide internal spelling.

Acceptance criteria:

• Maintainers agree on the tier definitions and audit rubric before
  individual tools are assigned production-readiness labels.
• A schema example handles a straightforward tool, a multi-backend tool, a
  method family such as hydrology, a wrapper/alias, and the existing GeoTIFF
  registry.
• The migration approach does not break
  xrspatial.geotiff.SUPPORTED_FEATURES.
• The resulting policy unambiguously explains when to use internal versus
  unsupported.

Phase 1: Build complete public-surface inventory

Deliverables:

• Generate/review an inventory from top-level exports, public subpackages,
  documented README rows, accessor methods, and reference pages.
• Reconcile gaps where something is exported but not documented, documented
  but not exported, duplicated under aliases, or intentionally experimental.
• Assign each inventory row a category owner and identify required
  subfeature overrides (backend, method, mode, integration).
• Seed the registry with all inventory rows at unclassified during the
  migration, or conservatively experimental if no transitional label is
  adopted.

Acceptance criteria:

• CI has a structural test that detects a newly exported/documented public
  tool lacking a registry entry.
• Every existing README tool row maps to a canonical registry entry or an
  explicit documented exclusion.
• Aliases and hydrology unified wrappers cannot produce conflicting claims
  with their canonical implementations.

Phase 2: Pilot outside GeoTIFF and validate the system

Choose several representative areas before batch-classifying the whole
library:

• a simple numerically defined family with broad backend coverage, such as
  multispectral indices or morphology;
• a backend/memory-sensitive family, such as focal operations or proximity;
• a method-rich family, such as hydrology;
• a geospatial integration family, such as reproject/resample.

Deliverables:

• Classify the selected callable and subfeature rows using the audit rubric.
• Add or identify evidence tests required to defend each initial tier.
• Render the first library-wide status documentation and update relevant
  docstrings/README rows to make the tier visible.
• Evaluate registry ergonomics, table readability, and whether the override
  level is too coarse or too granular.

Acceptance criteria:

• The pilot demonstrates how a user distinguishes core tool status from a
  backend or algorithm override.
• At least one real promotion gap is represented honestly rather than
  papered over by a broad label.
• Maintainers approve the schema/documentation presentation before bulk
  migration.

Phase 3: Batch classify every tool family

Create child issues or PR batches for each workstream listed above. Each
batch must:

• fill registry rows and subfeature overrides;
• state the default/recommended path and production guidance;
• cite current test evidence;
• add focused tests for claims that are cheap and clearly intended already;
• classify gaps conservatively and file promotion/hardening follow-ups rather
  than inflating the tier;
• update corresponding reference documentation and user-facing catalog
  presentation.

Required review questions for every batch:

• Are any README checkmarks being mistaken for parity/stability guarantees?
• Is a Dask or Dask+CuPy claim backed by chunk-boundary/laziness evidence?
• Is any GPU claim backed by a defined tolerance and device test strategy?
• Are algorithm variants bundled together despite different evidence?
• Are fallback modes and optional dependency behavior visible to users?
• Does any feature write files, download resources, consume network inputs,
  or accept complex vector/metadata inputs that require additional
  failure-mode coverage?

Acceptance criteria:

• Every public inventory row is classified.
• No tool appears as production-ready without stated scope and evidence.
• Known unstable or unsupported combinations are documented close to the
  callable and do not disappear inside a general tool label.

Phase 4: Documentation and discoverability rollout

Deliverables:

• Add a library-level feature tier/reference page, linked prominently from
  README and docs index, with filters/tables by category and tier.
• Add a compact tier column or badge to the README function catalog without
  obscuring the existing backend matrix.
• Add tier/status and scope to public API docstrings or generated API
  reference output, especially for advanced/experimental paths.
• Document how users inspect the registry programmatically.
• Add guidance for production workflows: use stable scope by default,
  understand advanced limitations, validate experimental behavior locally.
• Keep GeoTIFF pages linked as the detailed precedent rather than duplicating
  their full contract.

Acceptance criteria:

• A user can find a tool's tier from the README, reference docs, and runtime
  API/status registry.
• Docs and registry tiers cannot drift silently in CI.
• Advanced/experimental limitations are stated in the same page/section as
  the tier, not buried only in an issue.

Phase 5: Evidence gates and release process

Deliverables:

• Generalize the existing release_gate concept so stable non-GeoTIFF
  promises have lightweight, deterministic release-gate coverage or a
  documented CI suite that constitutes the gate.
• Add registry shape/completeness tests and doc parity tests.
• Establish backend parity/tolerance helpers so each family need not invent
  incompatible proof standards.
• Add release checklist steps: run stable gates, inspect skips/xfails,
  reconcile classification changes, and mention promotions/demotions in
  release notes.
• Define demotion handling when a stable or advanced promise is found false.

Acceptance criteria:

• Every stable classification cites passing tests appropriate to its stated
  scope.
• Stable gate failures block release or force an explicit corrected contract
  and release note; they cannot ship unnoticed.
• Skipped optional/GPU evidence is handled according to a written rule rather
  than silently counted as proof.

Phase 6: Promotion backlog and ongoing governance

Deliverables:

• Create follow-up issues for advanced/experimental features with concrete
  promotion requirements: missing parity matrices, reference comparisons,
  scalability limits, backend tests, error handling, or docs.
• Add contribution guidance requiring new public tools/subfeatures and new
  advertised backends to include a tier classification and evidence plan.
• Add a recurring release audit for tier promotions/demotions and stale
  experimental paths.
• Define a policy for retiring or moving long-lived experimental features
  that do not progress.

Acceptance criteria:

• New public functionality cannot be merged without a declared tier and
  visible status documentation.
• Promotions are evidence-driven PRs updating registry, tests, docs, and
  release notes together.
• The tier map remains a maintained product contract after the initial audit.

Test And Evidence Strategy

The initial audit may classify many features as advanced or experimental
because evidence is incomplete. It must not require exhaustive testing before
the registry exists. Evidence should scale with the promised tier:

Evidence type	Stable expectation	Advanced expectation	Experimental expectation
Basic functional tests	Required	Required	Smoke coverage
Invalid/boundary inputs	Required for documented contract	Important limitations covered	Add for serious risks
Reference/invariant comparison	Required where an algorithm has an objective reference/invariant	At least key cases	Optional/targeted
Backend parity/tolerance	Required for each backend claimed by stable scope	Document tested subset/gaps	No parity claim unless stated
Dask laziness/chunk behavior	Required when Dask is stable	Cover principal mode	Document uncertainty
GPU test execution	Required for stable GPU scope through available GPU CI/release gate	Smoke/parity where available, with skips visible	Smoke where practical
Scalability/resource bound	Required for memory/network/file-sensitive stable paths	Known limits documented	May be unknown but disclosed
Interoperability/security	Required where the stable feature touches external formats or inputs	Material checks/limits documented	Opt-in/fail loudly where hazardous

Runtime And API Design Requirements

• Do not add warnings on every normal call merely to announce that an
  advanced feature exists; that makes useful functionality noisy. Prefer
  discoverable registry/docs/docstrings.
• Use runtime opt-ins or warnings only for paths where accidental adoption
  has concrete consequences: misleading scientific results, non-interoperable
  output, hidden high costs, security exposure, or data loss.
• Do not demote a callable solely because one optional backend is less mature;
  represent backend-specific scope accurately.
• Do not label a callable stable when its default dispatch can unexpectedly
  select an experimental implementation without explicit user choice.
• Keep tier metadata lightweight and importable in minimal installations.

Deliverables Checklist

• Library-wide tier policy defining stable, advanced, experimental,
  internal, and unsupported.
• Canonical feature registry schema and public inspection API.
• Automated inventory/completeness check for public tools and accessors.
• Compatibility bridge or incorporation strategy for
  xrspatial.geotiff.SUPPORTED_FEATURES, including migration from
  internal_only to internal.
• Pilot classification PRs across representative tool families.
• Child audit issues/PRs for every library workstream.
• Complete classification of each public tool and meaningful subfeature.
• Library-level tier reference documentation and README discoverability.
• Registry/docs parity checks.
• Stable-contract tests/release-gate strategy beyond GeoTIFF.
• Release checklist and release-note rules for promotions/demotions.
• Contribution policy for new features and backend expansions.
• Promotion backlog for non-stable paths.

Epic Acceptance Criteria

• Every supported public tool/subfeature has a canonical, discoverable tier
  with explicit scope; internal paths and meaningful unsupported behavior are
  called out using the shared vocabulary.
• Users can determine production worthiness without reading implementation
  code or searching closed issues.
• A callable's backend availability matrix and its robustness tier no longer
  get conflated.
• Every stable claim points to test evidence and participates in the agreed
  release contract.
• Advanced and experimental claims state limitations and promotion work.
• Runtime registry, README/reference docs, and API documentation agree, with
  automated checks preventing drift.
• Existing GeoTIFF status remains compatible and becomes the first integrated
  example of the library-wide system, with an intentional compatibility path
  from internal_only to internal.
• New public tools and backend/mode additions must declare tier/evidence as
  part of review.

Suggested Child Issues

1. Policy/schema: define the five library statuses and design
   FEATURE_SUPPORT.
2. Inventory: reconcile exports, subpackages, accessors, README rows, and
   reference pages.
3. Compatibility: integrate/bridge xrspatial.geotiff.SUPPORTED_FEATURES
   and migrate/alias internal_only to internal.
4. Pilot: tier morphology/multispectral plus docs rendering.
5. Pilot: tier hydrology wrappers/algorithm variants and backend overrides.
6. Pilot: tier reproject/resample/merge integration behavior.
7. Audit terrain/surface/visibility.
8. Audit hydrology/flood after the pilot pattern is accepted.
9. Audit raster/vector, proximity, cost, and pathfinding.
10. Audit focal/neighborhood/image and diffusion functions.
11. Audit classification, multispectral/fire, KDE, interpolation,
    dasymetric, multivariate, and MCDA.
12. Audit utilities, diagnostics, accessors, optional dependencies, and
    fallback behavior.
13. Docs: add library feature-tier pages and update README/API visibility.
14. CI/release: registry completeness, docs parity, stable gates, and
    release checklist.
15. Governance: contribution rules and evidence-based promotion backlog.

Related Work

• #2340 established the GeoTIFF release contract and feature tiering.
• #2345 tracks GeoTIFF documentation and release-readiness audit practices.
• docs/source/reference/geotiff_release_contract.md defines the existing
  tier language and feature table.
• docs/source/reference/release_gate_geotiff.rst defines existing evidence
  and promote/demote release rules that this epic should generalize.